You currently do not have any folders to save your paper to! Create a new folder below.

Abstract

Optical remote sensing is the most widely used method for obtaining forest biomass information. This research investigated the potential of using topographical and high-resolution optical data from Quickbird for measurement of black locust plantation aboveground biomass (AGB) grown in the hill-gully region of the Loess Plateau. Three different processing techniques, including spectral vegetation indices (SVIs), texture, and topography were evaluated, both individually and combined. Simple linear regression and stepwise multiple-linear regression models were developed to describe the relationship between image parameters obtained using these approaches and field measurements. SVI and topography-based approaches did not yield reliable AGB estimates, accounting for at best 23 and 19% of the observed variation in AGB. Texture-based methods were better, explaining up to 70% of the observed variation. A combination of SVIs, texture, and topography yielded an even better R 2 value of 0.74 with the lowest root mean square error (17.21 t/ha ) and bias (−1.85 t/ha ). The results suggest that texture information from high-resolution optical data was more effective than SVIs and topography to estimate AGB. The performance of AGB estimation can be improved by adding SVIs and topography results to texture data; the best results can be obtained using a combination of these three data types.

Keywords/Phrases

Keywords

in

Remove

in

Remove

in

Remove

+ Add another field

Search In:

Proceedings

Volume

Journals +

Volume

Issue

Page

Journal of Applied Remote SensingJournal of Astronomical Telescopes Instruments and SystemsJournal of Biomedical OpticsJournal of Electronic ImagingJournal of Medical ImagingJournal of Micro/Nanolithography, MEMS, and MOEMSJournal of NanophotonicsJournal of Photonics for EnergyNeurophotonicsOptical EngineeringSPIE Reviews